code: def model(observed_data):
      mu_prior = Uniform(0.0, 1.0)
      mu = pyro.sample("mu", mu_prior)
  
      def observe_T(T_obs, obs_name):
          T_simulated = simulate(mu)
          T_obs_dist = Normal(
              T_simulated, torch.tensor(time_measurement_sigma)
          )
          pyro.sample(obs_name, T_obs_dist, obs=T_obs)
  
      for i, T_obs in enumerate(observed_data):
          observe_T(T_obs, "obs_%d" % i)
  
      return mu
  
file_path: pyro/examples/inclined_plane.py
imports: import argparse
  import numpy
  import torch
  import pyro
  from pyro.distributions import Normal, Uniform
  from pyro.infer import EmpiricalMarginal, Importance
label_desc: Use image node_id 3 for calling a global function with example usage: model(observed_data) and returns: mu